West Virginia and Kansas had the lowest cost of living across all U.S. states, with composite costs being half of those found in Hawaii. This was according to a composite index that compares prices for various goods and services on a state-by-state basis. In West Virginia, the cost of living index amounted to **** — well below the national benchmark of 100. Virginia— which had an index value of ***** — was only slightly above that benchmark. Expensive places to live included Hawaii, Massachusetts, and California. Housing costs in the U.S. Housing is usually the highest expense in a household’s budget. In 2023, the average house sold for approximately ******* U.S. dollars, but house prices in the Northeast and West regions were significantly higher. Conversely, the South had some of the least expensive housing. In West Virginia, Mississippi, and Louisiana, the median price of the typical single-family home was less than ******* U.S. dollars. That makes living expenses in these states significantly lower than in states such as Hawaii and California, where housing is much pricier. What other expenses affect the cost of living? Utility costs such as electricity, natural gas, water, and internet also influence the cost of living. In Alaska, Hawaii, and Connecticut, the average monthly utility cost exceeded *** U.S. dollars. That was because of the significantly higher prices for electricity and natural gas in these states.

This statistic shows the best states to make living in the United States in 2019. In 2019, Wyoming was ranked as the best state to make a living in the United States, with the cost of living index at **** value and the median income of ****** U.S. dollars.

This statistic shows the most affordable metro areas in the Unites States in 2017, by share of income spent on living expenses. In 2017, Omaha was the second most affordable metro area because ***** percent of the median blending annual household income was spent on the average cost of owning or renting a home as well the average cost of utilities and taxes.

In 2024, the annual cost for a private room in an assisted living facility in the U.S. amounted to ****** U.S. dollars - the national median price. However, cost varied greatly from one state to another. The least expensive states for a private room in assisted living were South Dakota, and Mississippi. While the most expensive states for assisted living were Hawaii and Alaska.

The poly shapefile shows income levels needed to support a family of four living in the high-cost of living areas within the states. It also shows percent income above the Federal poverty levels ($20,650 = 100%)

This table contains data on the percent of households paying more than 30% (or 50%) of monthly household income towards housing costs for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Department of Housing and Urban Development (HUD), Consolidated Planning Comprehensive Housing Affordability Strategy (CHAS) and the U.S. Census Bureau, American Community Survey (ACS). The table is part of a series of indicators in the [Healthy Communities Data and Indicators Project of the Office of Health Equity] Affordable, quality housing is central to health, conferring protection from the environment and supporting family life. Housing costs—typically the largest, single expense in a family's budget—also impact decisions that affect health. As housing consumes larger proportions of household income, families have less income for nutrition, health care, transportation, education, etc. Severe cost burdens may induce poverty—which is associated with developmental and behavioral problems in children and accelerated cognitive and physical decline in adults. Low-income families and minority communities are disproportionately affected by the lack of affordable, quality housing. More information about the data table and a data dictionary can be found in the Attachments.

In 2019, the state of California had the least affordable child care for school-aged children. The cost of care is presented as a percentage of state median income for a two-parent family. A two-parent family, living in the state, spent 19 percent of their median income for full-time care of a school-aged child in a child care center.

Alabama cost of living for the counties with the lowest and highest MHI in Alabama (2022 U.S. Dollars).

VITAL SIGNS INDICATOR Poverty (EQ5)

FULL MEASURE NAME The share of the population living in households that earn less than 200 percent of the federal poverty limit

LAST UPDATED December 2018

DESCRIPTION Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

DATA SOURCE U.S Census Bureau: Decennial Census http://www.nhgis.org (1980-1990) http://factfinder2.census.gov (2000)

U.S. Census Bureau: American Community Survey Form C17002 (2006-2017) http://api.census.gov

METHODOLOGY NOTES (across all datasets for this indicator) The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. Poverty rates do not include unrelated individuals below 15 years old or people who live in the following: institutionalized group quarters, college dormitories, military barracks, and situations without conventional housing. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or noncash benefits (such as public housing, Medicaid, and food stamps). For the national poverty level definitions by year, see: https://www.census.gov/hhes/www/poverty/data/threshld/index.html For an explanation on how the Census Bureau measures poverty, see: https://www.census.gov/hhes/www/poverty/about/overview/measure.html

For the American Community Survey datasets, 1-year data was used for region, county, and metro areas whereas 5-year rolling average data was used for city and census tract.

To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

The housing affordability measure illustrates the relationship between income and housing costs. A household that spends 30% or more of its collective monthly income to cover housing costs is considered to be “housing cost-burden[ed].”[1] Those spending between 30% and 49.9% of their monthly income are categorized as “moderately housing cost-burden[ed],” while those spending more than 50% are categorized as “severely housing cost-burden[ed].”[2]

How much a household spends on housing costs affects the household’s overall financial situation. More money spent on housing leaves less in the household budget for other needs, such as food, clothing, transportation, and medical care, as well as for incidental purchases and saving for the future.

The estimated housing costs as a percentage of household income are categorized by tenure: all households, those that own their housing unit, and those that rent their housing unit.

Throughout the period of analysis, the percentage of housing cost-burdened renter households in Champaign County was higher than the percentage of housing cost-burdened homeowner households in Champaign County. All three categories saw year-to-year fluctuations between 2005 and 2023, and none of the three show a consistent trend. However, all three categories were estimated to have a lower percentage of housing cost-burdened households in 2023 than in 2005.

Data on estimated housing costs as a percentage of monthly income was sourced from the U.S. Census Bureau’s American Community Survey (ACS) 1-Year Estimates, which are released annually.

As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes a dataset on Housing Tenure.

[1] Schwarz, M. and E. Watson. (2008). Who can afford to live in a home?: A look at data from the 2006 American Community Survey. U.S. Census Bureau.

[2] Ibid.

Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (17 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (22 September 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (30 September 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (10 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (10 June 2021).;U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; 16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).

VITAL SIGNS INDICATOR
Poverty (EQ5)

FULL MEASURE NAME
The share of the population living in households that earn less than 200 percent of the federal poverty limit

LAST UPDATED
January 2023

DESCRIPTION
Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

DATA SOURCE
U.S Census Bureau: Decennial Census - http://www.nhgis.org
1980-2000

U.S. Census Bureau: American Community Survey - https://data.census.gov/
2007-2021
Form C17002

CONTACT INFORMATION
vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator)
The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or non-cash benefits (such as public housing, Medicaid and food stamps).

For the national poverty level definitions by year, see: US Census Bureau Poverty Thresholds - https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-poverty-thresholds.html.

For an explanation on how the Census Bureau measures poverty, see: How the Census Bureau Measures Poverty - https://www.census.gov/topics/income-poverty/poverty/guidance/poverty-measures.html.

American Community Survey (ACS) 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020.

To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

Graph and download economic data for Estimated Mean Real Household Wages Adjusted by Cost of Living for Lake County, OH (MWACL39085) from 2009 to 2023 about Lake County, OH; Cleveland; adjusted; OH; average; wages; real; and USA.

In the United States, Hawaii was the state with the most expensive housing, with the typical value of single-family homes in the 35th to 65th percentile range exceeding ******* U.S. dollars. Unsurprisingly, Hawaii also ranked top as the state with the highest cost of living. Meanwhile, a property was the least expensive in West Virginia, where it cost under ******* U.S. dollars to buy the typical single-family home. Single-family home prices increased across most states in the United States between December 2023 and December 2024, except in Louisiana, Florida, and the District of Colombia. According to the Federal Housing Association, house appreciation in 13 states exceeded **** percent in 2023.

This table contains data on the living wage and the percent of families with incomes below the living wage for California, its counties, regions and cities/towns. Living wage is the wage needed to cover basic family expenses (basic needs budget) plus all relevant taxes; it does not include publicly provided income or housing assistance. The percent of families below the living wage was calculated using data from the Living Wage Calculator and the U.S. Census Bureau, American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. The living wage is the wage or annual income that covers the cost of the bare necessities of life for a worker and his/her family. These necessities include housing, transportation, food, childcare, health care, and payment of taxes. Low income populations and non-white race/ethnic have disproportionately lower wages, poorer housing, and higher levels of food insecurity. More information about the data table and a data dictionary can be found in the About/Attachments section.

Manufactured Homes Market Outlook

The global manufactured homes market is projected to grow significantly over the forecast period, with a market size estimated at USD 28.5 billion in 2023 and expected to reach USD 47.1 billion by 2032, registering a compound annual growth rate (CAGR) of 5.6%. The growth factor is driven primarily by the increasing demand for affordable housing solutions, coupled with advancements in manufacturing technologies that make these homes more durable and aesthetically pleasing.

One of the primary growth factors for the manufactured homes market is affordability. Manufactured homes offer a cost-effective alternative to traditional site-built homes. The average cost of a manufactured home is significantly lower due to streamlined production processes and bulk purchasing of materials. This affordability makes them an attractive option for first-time homebuyers, retirees, and low-income families who may find it challenging to purchase traditional homes. Additionally, the cost of land and property taxes are often lower for manufactured homes, further enhancing their appeal.

Innovations in construction technologies and materials have also been pivotal in driving the market. Modern manufactured homes are built using high-quality materials and advanced construction techniques, making them more energy-efficient and resilient. Improvements in insulation, roofing, and HVAC systems have made these homes more sustainable and comfortable. Moreover, smart home integrations are becoming more common in manufactured homes, appealing to tech-savvy buyers looking for modern amenities at a fraction of the cost of traditional homes.

The growing trend toward sustainable living is another critical growth driver. As consumers become more environmentally conscious, the demand for eco-friendly housing solutions is rising. Manufactured homes can be designed with sustainable materials and energy-efficient systems, reducing their environmental footprint. Furthermore, the manufacturing process itself tends to generate less waste compared to traditional construction methods. This sustainable aspect aligns well with global efforts to combat climate change and reduce carbon emissions.

Regionally, North America dominates the manufactured homes market, driven by high demand in the United States, where manufactured housing is a popular option for affordable living. The market in Europe is also expanding, particularly in countries with stringent housing regulations and high real estate prices, such as the UK and Germany. The Asia Pacific region is anticipated to witness the highest growth rate, owing to urbanization and the need for affordable housing solutions in countries like India and China.

Product Type Analysis

The manufactured homes market can be segmented by product type into single-section and multi-section homes. Single-section homes, often referred to as "single-wides," are more compact and typically cover less than 1,000 square feet. These homes are easier to transport and set up, making them a popular choice for individuals or small families. Single-section homes tend to be more affordable due to their smaller size and simpler design, which makes them an attractive option for budget-conscious buyers.

Multi-section homes, also known as "double-wides" or "triple-wides," offer more space and can cover up to 3,000 square feet or more. These homes are designed with multiple sections that are assembled on-site. The extra space in multi-section homes allows for more customization and the inclusion of additional amenities such as larger kitchens, multiple bathrooms, and extra bedrooms. This makes them suitable for larger families or individuals looking for more spacious living accommodations.

The market for multi-section homes is growing faster than single-section homes due to their resemblance to traditional site-built homes. They offer a higher level of comfort and luxury while still being more affordable than conventional housing. The flexibility in design and increased living space make multi-section homes an appealing option for a broader range of consumers. Additionally, advancements in construction technology have made it easier to manufacture and assemble these larger units, further boosting their popularity.

In terms of market share, multi-section homes hold a larger portion due to the high demand for more spacious living solutions. However, single-section homes continue to maintain a significant presence, particularly in rural areas where land is

Graph and download economic data for Estimated Mean Real Household Wages Adjusted by Cost of Living for Spokane County, WA (MWACL53063) from 2009 to 2023 about Spokane County, WA; Spokane; adjusted; WA; average; wages; real; and USA.

Of the most populous cities in the U.S., San Jose, California had the highest annual income requirement at ******* U.S. dollars annually for homeowners to have an affordable and comfortable life in 2024. This can be compared to Houston, Texas, where homeowners needed an annual income of ****** U.S. dollars in 2024.

In 2024, the average daily cost for adult day health care services in the U.S. stood at 100 U.S. dollars. However, such costs varied greatly from one state to another. In that year, the most expensive state for adult day health care services was by far Oregon, amounting to 284 U.S. dollars a day, while in Delaware daily rates were just 35 U.S. dollars. In the most expensive states, the daily cost of adult day care actually exceeded that of assisted living facilities and sometimes even home health care. The large variation may be in part due to the source using community subsidy rates where available, thus lower rates were reported, while states with higher rates may capture the full private pay rates.

United States PCE Inflation Nowcast: sa: Contribution: Commodity Prices: Live Cattle Futures: CME: Settlement Price: 1st Month data was reported at 0.000 % in 12 May 2025. This stayed constant from the previous number of 0.000 % for 05 May 2025. United States PCE Inflation Nowcast: sa: Contribution: Commodity Prices: Live Cattle Futures: CME: Settlement Price: 1st Month data is updated weekly, averaging 0.000 % from Apr 2019 (Median) to 12 May 2025, with 320 observations. The data reached an all-time high of 18.073 % in 25 Mar 2024 and a record low of 0.000 % in 12 May 2025. United States PCE Inflation Nowcast: sa: Contribution: Commodity Prices: Live Cattle Futures: CME: Settlement Price: 1st Month data remains active status in CEIC and is reported by CEIC Data. The data is categorized under Global Database’s United States – Table US.CEIC.NC: CEIC Nowcast: Personal Consumption Expenditure (PCE) Inflation: Headline.

United States CPI U: Housing: HFO: FB: Living Room, Kitchen & Dining Furniture data was reported at 85.927 Dec1997=100 in Jun 2018. This records a decrease from the previous number of 86.130 Dec1997=100 for May 2018. United States CPI U: Housing: HFO: FB: Living Room, Kitchen & Dining Furniture data is updated monthly, averaging 91.316 Dec1997=100 from Dec 1997 (Median) to Jun 2018, with 247 observations. The data reached an all-time high of 103.900 Dec1997=100 in Nov 2000 and a record low of 83.389 Dec1997=100 in Nov 2017. United States CPI U: Housing: HFO: FB: Living Room, Kitchen & Dining Furniture data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.I002: Consumer Price Index: Urban.